Kmeans Implementation

About The Project

We implemented the 2D Kmeans algorithm in three different ways:

1. A sequential mode in Python
2. A Parallel mode in OpenMP
3. A Parallel mode in Cuda

Built With

• Python
• OpenMP
• CUDA

For more information, read the report or the presentation

Getting Started

In order to get a local copy and run some tests, follow these simple steps.

1. Clone the repo

git clone https://github.com/FedeNoce/Kmeans.git

2. Chose the implementation: kmeans_seq.py for sequential, Kmeans_openMp.cpp for parallel with OpenMP, 2D_kmeans_cuda.cu for parallel with CUDA.
3. Choose the dataset and copy the file path in the code
4. Set the parameters with your settings
5. Run the tests
6. Evaluate the clustering of the tests running evaluate_kmeans.py

Authors

• Corso Vignoli
• Federico Nocentini

Acknowledgments

Parallel Computing © Course held by Professor Marco Bertini - Computer Engineering Master Degree @University of Florence